[HTML][HTML] Mutual benefits: Combining reinforcement learning with sequential sampling models
Reinforcement learning models of error-driven learning and sequential-sampling models of
decision making have provided significant insight into the neural basis of a variety of …
decision making have provided significant insight into the neural basis of a variety of …
Thinking in and about time: A dual systems perspective on temporal cognition
We outline a dual systems approach to temporal cognition, which distinguishes between two
cognitive systems for dealing with how things unfold over time–a temporal updating system …
cognitive systems for dealing with how things unfold over time–a temporal updating system …
Improving the reliability of model-based decision-making estimates in the two-stage decision task with reaction-times and drift-diffusion modeling
A well-established notion in cognitive neuroscience proposes that multiple brain systems
contribute to choice behaviour. These include:(1) a model-free system that uses values …
contribute to choice behaviour. These include:(1) a model-free system that uses values …
A new model of decision processing in instrumental learning tasks
Learning and decision-making are interactive processes, yet cognitive modeling of error-
driven learning and decision-making have largely evolved separately. Recently, evidence …
driven learning and decision-making have largely evolved separately. Recently, evidence …
Learning about reward identities and time
We discuss three empirical findings that we think any theory attempting to integrate interval
timing with associative learning concepts will need to address. These empirical phenomena …
timing with associative learning concepts will need to address. These empirical phenomena …
How do real animals account for the passage of time during associative learning?
VMK Namboodiri - Behavioral neuroscience, 2022 - psycnet.apa.org
Animals routinely learn to associate environmental stimuli and self-generated actions with
their outcomes such as rewards. One of the most popular theoretical models of such …
their outcomes such as rewards. One of the most popular theoretical models of such …
Contingency, contiguity, and causality in conditioning: Applying information theory and Weber's Law to the assignment of credit problem.
Contingency is a critical concept for theories of associative learning and the assignment of
credit problem in reinforcement learning. Measuring and manipulating it has, however, been …
credit problem in reinforcement learning. Measuring and manipulating it has, however, been …
Adapting the flow of time with dopamine
The modulation of interval timing by dopamine (DA) has been well established over
decades of research. The nature of this modulation, however, has remained controversial …
decades of research. The nature of this modulation, however, has remained controversial …
Reinforcement learning with associative or discriminative generalization across states and actions: fMRI at 3 T and 7 T
The model‐free algorithms of “reinforcement learning”(RL) have gained clout across
disciplines, but so too have model‐based alternatives. The present study emphasizes other …
disciplines, but so too have model‐based alternatives. The present study emphasizes other …
[HTML][HTML] Mild exogenous inflammation blunts neural signatures of bounded evidence accumulation and reward prediction error processing in healthy male participants
F Queirazza, J Cavanagh, MG Philiastides… - Brain, Behavior, and …, 2024 - Elsevier
Background Altered neural haemodynamic activity during decision making and learning has
been linked to the effects of inflammation on mood and motivated behaviours. So far, it has …
been linked to the effects of inflammation on mood and motivated behaviours. So far, it has …